Ensemble streamflow prediction considering the influence of reservoirs in Narmada River Basin, India

[摘要] Developing an ensemble hydrological prediction system is essential forreservoir operations and flood early warning. However, efforts to buildhydrological ensemble prediction systems considering the influence ofreservoirs have been lacking in India. We examine the potential of theExtended Range Forecast System (ERFS, 16 ensemble members) and GlobalEnsemble Forecast System (GEFS, 21 ensemble members) forecast for streamflowprediction in India using the Narmada River Basin as a test bed. We use thevariable infiltration capacity (VIC) with reservoir operations (VIC-Res)scheme to simulate the daily river flow at four locations in the NarmadaBasin. Streamflow prediction skills of the ERFS forecast were examined forthe period 2003–2018 at 1–32 d lead. We compared the streamflow forecastskills of raw meteorological forecasts from ERFS and GEFS at a 1–10 d lead for the summer monsoon (June–September) 2019–2020. The ERFS forecastunderestimates extreme precipitation against the observations compared tothe GEFS forecast during the summer monsoon of 2019–2020. However, both forecast products show better skills for minimum and maximum temperaturesthan precipitation. Ensemble streamflow forecast from the GEFS performsbetter than the ERFS during 2019–2020. The performance of GEFS-basedensemble streamflow forecast declines after 5 days lead. Overall, theGEFS ensemble streamflow forecast can provide reliable skills at a 1–5 dlead, which can be utilized in streamflow prediction. Our findings providedirections for developing a flood early warning system based on ensemblestreamflow prediction considering the influence of reservoirs in India.

[学科分类] 妇产科学